Fall semester:

  • Biochemistry I is the combinations of the following three courses (graduate students will have higher requirements than undergraduate students):

50:115:403    General Biochemistry I (undergraduate course)

56:115:511    Biochemistry I (graduate course)

56:121:510    Essential Biological Chemistry (graduate course)

Rationale: This class will be an advanced overview of general biochemistry. Upon completion of this course, the student should have a better understanding of the principle of protein structure, physical interaction between proteins, catalysis, regulation of catalysis, protein synthesis and energy metabolism.

Topics to be covered: The biochemistry class is to develop a deep understanding of 1) the major bio-molecules found in living organisms; 2) the control and regulation of protein structure and function; 3) enzyme kinetics; 4) lipids and membrane transport; 5) carbohydrates and 6) basic knowledge of drug discovery

The topics will be taught in this class will include but not limit to the following topics:

1)      structure and chemical reactions associated with biological molecules;

2)      amino acids;

3)      basic elements of protein structure;

4)      structure of different classes of lipids;

5)      enzyme kinetics;

6)      nucleic acids

Required Textbook: Voet & Voet, Biochemistry (Wiley) 4th Edition (2010) (ISBN # 978-0-470-57095-1 )

biochemistry bookzhu_biochemistry_syllabus

  • Pharmaceutical Chemistry (56:160:515) (graduate course)

Rational:

Drug research is a supremely challenging mission since the numerous attributes of drug molecules need to be simultaneously optimized. This class will focus on the drug likeness of chemicals. Absorption, Distribution, Metabolism and Exclusion (ADME) and toxicity are those critical reasons to determine a compound to be an efficacious drug-like compound or not. Not only chemists but biologists/pharmacologists will benefit from understanding ADME/Tox concepts. The application of ADME/Tox research has been expanded from optimizing in vivo pharmacokinetics and safety to designing proper bioassay protocols. This class is to teach the students who will have the potentials to be engaged in the research and design process of new drugs.

Topics to be covered:

Basic concepts of biochemistry

Effects of physical properties of chemicals (solubility, partition coefficients, and acid/base) on their biological effects.

Structure-activity relationships (configuration, conformation, polarity)

Adsorption, distribution, metabolism and excretion of xenobiotic compounds

Mechanisms for toxicity (acute, carcinogenesis, developmental, genetic)

Pharmacokinetics

Endocrinology and physiology as needed

Historical origins and key experiments in the development of ideas about drugs and toxins

Statistical methods commonly used in biomedical research, as used in examples drawn from primary literature.

Current topics in drug development and toxicology, production processes, economic/political linkages, regulations.

Required Textbook: Drug-like Properties: Concepts, Structure Design and Methods-from ADME to Toxicity Optimization by Kerns and Di, ISBN 978-0-1236-9520-8

                             Foye’s Principles of Medicinal Chemistry 7th ed., by Lemke, Williams, Roche and Zito, ISBN 978-1-60913-345-0

pharmaceutical chemistry bookpharmaceutical chemistry book2zhu_pharm_chem_syllabus

Spring semester:

  • Cheminformatics (56:121:555) (graduate course)

Rationale: Cheminformatics has been defined as the science of examining the structure and function of chemicals through the use of computational analysis, statistics, and pattern recognition. A number of recent workforce studies have shown that there is a high current and unmet demand for people trained to various levels of expertise in informatics, from technicians and technical librarians to developers of new and improved methodologies and applications.

 

Course Description:The course will majorly teach the cheminformatics algorithms, workflows and other relevant computational tools that the students may use or access in the future Computer-Aided Drug Discovery (CADD) work of pharmaceutical companies and academic institutes. The important knowledge of the second part of class includes chemical descriptors, chemical similarity, Quantitative Structure Activity Relationship (QSAR) modeling, model applicability domain and virtual screening. The students will learn how to use the knowledge of cheminformatics to create the QSAR models and use the models to identify novel drug like compounds.

Several popular computational tools and modeling approaches, such as Molecular Operating Environment (MOE) (www.chemcomp.com), Random Forest (RF), Support Vector Machine (SVM) and k Nearest Neighbor (kNN) will be involved in this class. Students are encouraged to examine the implementation of all the knowledge they learn from the lectures by using these tools and approaches during the lab time. Furthermore, the information covered in lectures will be expanded upon and reinforced by group discussions and the use of available computational resources.

Course Objectives: Upon completion of this course, the student should be able to:

  1. Have the knowledge of the basic ligand/structure based drug design approaches.
  2. Understand the basic algorithms used in the established software to carry out the most common CADD project.
  3. Understand the importance of proper use of various parameters in cheminformatics application programs.
  4. Practical use of various computational tools available for computer aided drug design including 2D/3D structural database.

zhu_cheminformatics_syllabus